This paper provides an overview of forward dynamic neuromusculoskeletal modeling. The aim of such models is to estimate or predict muscle forces, joint moments, and/or joint kinematics from neural signals. This is a four-step process. In the first step, muscle activation dynamics govern the transformation from the neural signal to a measure of muscle activation-a time varying parameter between 0 and 1. In the second step, muscle contraction dynamics characterize how muscle activations are transformed into muscle forces. The third step requires a model of the musculoskeletal geometry to transform muscle forces to joint moments. Finally, the equations of motion allow joint moments to be transformed into joint movements. Each step involves complex nonlinear relationships. The focus of this paper is on the details involved in the first two steps, since these are the most challenging to the biomechanician. The global process is then explained through applications to the study of predicting isometric elbow moments and dynamic knee kinetics. Keywords Hill model; EMG; tendon; musculotendon complex; pennation angleThe eight-syllable term neuromusculoskeletal in the title of this article simply means that we will be modeling the movements produced by the muscular and skeletal systems as controlled by the nervous system. Neuromusculoskeletal modeling is important for studying functional electrical stimulation of paralyzed muscles, for designing prototypes of myoelectrically controlled limbs, and for general study of how the nervous system controls limb movements in both unimpaired people and those with pathologies such as spasticity induced by stroke or cerebral palsy.There are two fundamentally different approaches to studying the biomechanics of human movement: forward dynamics and inverse dynamics. Either approach can be used to determine joint kinetics (e.g., estimate joint moments during movements) and it is important that the differences between them are understood.NIH Public Access
To study abnormal spatial patterns of muscle activation in hemiparetic stroke, we compared EMG activity in paretic and contralateral elbow and shoulder muscles of 10 hemiparetic subjects during 1.5-s voluntary isometric contractions, against five to eight different loads. Isometric forces were generated in eight directions, referenced to a plane orthogonal to the long axis of the forearm, and were recorded by a three degrees of freedom load cell, mounted at the wrist. Surface and intramuscular EMGs of six elbow and six shoulder muscles were recorded from both impaired and contralateral upper extremities of each subject. The spatial characteristics of EMG activation of individual muscles were summarized using two measures. The first, called the 'net resultant EMG vector' is a new measure which calculated the vector sum of EMG magnitudes for each of the eight directions, and the second, index of EMG focus, is a measure of the range of EMG activation recorded for each load level. Use of these measures permitted us to describe spatial EMG characteristics quantitatively, which has not been done previously. We observed consistent and statistically significant shifts in the resultant EMG vector directions in the impaired limb, especially in shoulder and other proximal muscles. Significant increases in the angular range of EMG activity were also identified and were most evident at the elbow. Correlation analysis techniques were used to assess the degree of coactivation of different muscle pairs. There were consistent EMG coactivation patterns observed across all subjects (both normal and hemiparetic). However, in spasticparetic limbs, additional novel coactivational relationships were also recorded, especially between elbow flexors/shoulder abductors and elbow extensors/shoulder adductors. These novel coactivation patterns represent a reduction in the number of possible muscle combinations, or in the number of possible 'synergies' in the paretic limb of the stroke subject. This reduction in number of 'synergies' could result from a loss of descending command options; from an increased reliance on residual, descending brainstem pathways (such as the reticulospinal and vestibulospinal projections); from changes in spinal interneuronal excitability; or from a combination of several of these factors. The relative merits of these hypotheses are addressed.
Some individuals can stabilize their knees following anterior cruciate ligament rupture even during activities involving cutting and pivoting (copers), others have instability with daily activities (non-copers). Movement and muscle activation patterns of 11 copers, ten non-copers and ten uninjured subjects were studied during walking and jogging. Results indicate that distinct gait adaptations appeared primarily in the non-copers. Copers used joint ranges of motion, moments and muscle activation patterns similar to uninjured subjects. Non-copers reduced their knee motion, and external knee flexion moments that correlated well with quadriceps strength. Non-copers also achieved peak hamstring activity later in the weight acceptance phase and used a strategy involving more generalized co-contraction. Both copers and non-copers had high levels of quadriceps femoris muscle activity. The reduced knee moment in the involved limbs of the non-copers did not represent "quadriceps avoidance" but rather represented a strategy of general co-contraction with a greater relative contribution from the hamstring muscles.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.